Deep Learning Research Engineer

WAIR is an Amsterdam-based logistics technology company transforming inventory management in the fashion retail sector through AI. Our flagship product, the AI Forecaster, integrates seamlessly with existing enterprise resource planning systems (ERP) as a software as a service (SaaS) add-on, providing precise inventory adjustments on demand. By harnessing advanced time-series analysis and deep learning, WAIR automates and optimizes existing logistic processes like initial distribution, replenishment, and redistribution, reducing waste and boosting profitability. We are dedicated to democratizing advanced AI, empowering businesses of all sizes to compete effectively. Our unique “stronger together” approach, enabled by our cross-client data pooling methodology, reveals patterns and insights that individual retailers cannot uncover alone, driving unprecedented efficiency and strategic advantage. Become part of our ambitious team at a pivotal moment as we transition from startup to scale-up, and contribute to the next wave of AI-driven transformation in retail logistics.

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Research Team

As a member of WAIR’s research team, you will be at the forefront of our AI strategy, driving the innovation that shapes the future of our products. Our team operates on a projectbased approach, alternating applied R&D – such as developing segmentation strategies for product images – with more fundamental scientific research, as demonstrated in publications like this one, where we approach forecasting with in-context learning. With the autonomy to set our own research agenda, you’ll have the unique opportunity to steer the AI vision of the company while working on projects that directly influence the industry.

Responsibilities

  • Prototype Development and Experimentation: Conduct research and experimentation on the most challenging open questions that come up in practice, providing insights that drive forward the company’s AI solutions. Actively engage with
    other teams to identify these research needs. Then, conceptualize and develop innovative solutions for downstream use in the Applied ML team.
  • Scientific Contributions: Contribute to high-quality scientific papers and other publications that showcase our research, elevating WAIR’s standing in both academic and professional AI communities. Apply rigorous scientific methods
    to ensure robust, credible outcomes that advance the field and reinforce our reputation as a leader in AI innovation.
  • Model Scaling and Optimization: Take part in our team’s journey to effectively scale the training of large models, optimizing training data ingestion pipelines and GPU runtimes. Maintain cost-effectiveness while optimizing model
    performance.
  • Knowledge Building: Stay at the forefront of both practical and theoretical AI advancements. Regularly present and share your research findings with the team, fostering a culture of continuous learning and collaboration while
    actively expanding the company’s knowledge base.
  • Evaluation and Analysis: Enhance evaluation methods and analysis of datasets and models using data science techniques and explainable AI, driving more accurate understanding of the problem we are solving as a company

Your Profile

We are seeking a candidate who embodies the following qualities and qualifications:

  • Collaboration: Strong communication skills are essential in our close-knit research team, which thrives on brainstorming, workshops, and frequent presentations.
  • Technical Expertise: Proficient in ML-science and -engineering best practices, with an understanding of the challenges in scaling to large datasets or models. You are comfortable with building DL models in tools like PyTorch or
    Tensorflow, building and optimizing training data pipelines, creating docker images for a proptype’s API, and solving mathematical challenges on the whiteboard when needed.
  • Openness: We value honesty, transparency, and a willingness to present results accurately, even if they fall short of expectations. Creativity and a willingness to explore new ideas are also highly prized.
  • Experience: Several years of hands-on experience with deep learning models and their successful application in real-world scenarios. We welcome applications from both mid-level and senior professionals.
  • Research-Driven: A passion for R&D with a strong commitment to project completion. Self-motivation and the ability to acquire new technical skills are critical.
  • Education: A relevant degree in machine learning, mathematics, physics, computer science, or a related field.

Nice-to-haves:

The following points are a nice addition to your application but not essential:

  • Research Experience: Prior research experience, such as in a Ph.D. program or a research-focused position.
  • Large Model Experience: Prior experience scaling model concepts up, such as in for example LLMs or other Gen-AI, with a focus on training them successfully.

What We Offer

  • Competitive Salary: We value expertise and ensure you are compensated fairly.
  • Flexible & Hybrid Working: Enjoy the flexibility to work from home or the office as needed, with hours that accommodate your lifestyle
  • Impactful Contributions: Your voice matters here. Play a key role in shaping the future direction of our company, and the kind of projects we work on as a team.
  • State-of-the-art: An opportunity to work with and on cutting-edge AI developments, offering the creative freedom and academic engagement of research, combined with the engineering excellence and industry exposure of a product
    company.